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'''Workforce modeling''' is the process of aligning the [[demand]] for skilled labor with the availability and preferences of [[skilled workers]] ([[Supply and demand|supply]]). It uses mathematical models to support tasks such as [[sensitivity analysis]], scheduling, and workload forecasting.
This approach is commonly applied in industries with complex labor regulations, certified workers, and varying levels of demand, including healthcare, public safety, and retail. Workforce modeling solutions often include software tools that help determine staffing needs based on workload volume across different periods, such as times of day, days of the week, or seasonal cycles.
==Definition==
{{Unreferenced section|date=May 2025|small=y}}
The term can be differentiated from traditional staff [[Schedule (workplace)|scheduling]]. Staff scheduling is rooted in [[time management]]. Besides demand orientation, workforce modeling also incorporates the forecast of the workload and the required staff, the integration of workers into the scheduling process through interactivity, and analysis of the entire process.{{citation needed|date=June 2025}}
==Complexity of the model==
Many applications providing a workforce modeling solution use the [[linear programming]] approach to create the Workforce Model. Linear methods of achieving a schedule are generally based on assumptions that demand is based on a series of independent events, each with a consistent, predictable outcome. However, modeling the uncertainty and dependability of these events is a well-researched area.<ref name="Clancy, Thomas R. 2008">Clancy, Thomas R. ''Managing Organizational Complexity in Healthcare Operations.'' [[The Journal of Nursing Administration 38.9 (2008): 367–370. Print.]]</ref> Modeling approaches such as [[system dynamics]] have also been employed in workforce modeling to address interdependencies and feedback loops within large organizations, such as [[NASA]].<ref name=":0">{{Cite journal |last=Marin |first=Mario |last2=Zhu |first2=Yanshen |last3=Meade |first3=Phillip |last4=Sargent |first4=Melissa |last5=Warren |first5=Jullie |date=2007 |title=Workforce Enterprise Modeling |url=https://www.jstor.org/stable/44719519 |journal=SAE Transactions |volume=116 |pages=873–876 |issn=0096-736X}}</ref> [[Heuristic|Heuristics]] have also been applied to the problem, and [[metaheuristics]] have been identified as effective methods for generating complex scheduling solutions.<ref name="Clancy, Thomas R. 2008" /><ref>{{Cite journal |last1=Burke |first1=Edmund |last2=Causmaecker |first2=Patrick De |last3=Berghe |first3=Greet Vanden |last4=Landeghem |first4=Hendrik Van |date=2004 |title=The State of the Art of Nurse Rostering |url=https://lirias.kuleuven.be/bitstream/123456789/123829/1/JOS_ |url-status=dead |journal=Journal of Scheduling |volume=7 |issue=441–499 |pages=441–499 |doi=10.1023/B:JOSH.0000046076.75950.0b |archive-url=https://web.archive.org/web/20160304113501/https://lirias.kuleuven.be/bitstream/123456789/123829/1/JOS_ |archive-date=March 4, 2016|url-access=subscription }}</ref>
Workforce modeling solutions can be created using a [[software]] solution for demand-oriented workforce management.
==== Incorporation of AI and Machine Learning ====
===== AI's Impact on Employment: =====
Anthropic CEO Dario Amodei warned that AI could eliminate up to 50% of entry-level white-collar jobs and raise unemployment to 10–20% within five years. This highlights the significant impact AI could have on workforce dynamics. [https://www.axios.com/2025/05/30/ai-jobs-replace-humans-ceos-amodei <nowiki>[Source]</nowiki>]
==== Workforce Management Software Market Growth ====
The workforce management software market is projected to grow by USD 3.67 billion between 2025 and 2029, driven by regulatory compliance and AI-powered market evolution. [https://www.prnewswire.com/news-releases/workforce-management-software-market-to-grow-by-usd-3-67-billion-2025-2029-boosted-by-regulatory-compliance-market-evolution-powered-by-ai---technavio-302370194.html <nowiki>[Source]</nowiki>]
== Integration with Financial Planning and Strategic Objectives ==
==== Michigan's AI Workforce Plan: ====
Michigan's Department of Labor and Economic Opportunity released an AI and Workforce Plan aiming to create up to 130,000 good-paying jobs and gain up to $70 billion in economic impact over the next 5 to 10 years. The plan focuses on integrating AI into workforce planning and economic strategies. [https://www.michigan.gov/leo/news/2025/05/29/ai-and-the-workforce-plan-will-create-jobs-invest-in-workforce-and-enhance-economic-growth <nowiki>[Source]</nowiki>]
== Real-World Applications and Case Studies ==
==== Media Industry: ====
Business Insider laid off approximately 21% of its workforce, aiming to restructure the company towards a more AI-driven future. CEO Barbara Peng stated that over 70% of employees already use Enterprise ChatGPT, with a goal of 100% adoption. [https://www.sfgate.com/bayarea/article/business-insider-ai-laying-off-staff-20353086.php <nowiki>[Source]</nowiki>]
==Notes==
<references/>
==Further reading==
*Sterman JD. ''Business Dynamics: Systems Thinking and Modeling For a Complex World.'' Boston, Massachusetts: McGraw-Hill Publishers; 2000.
*Taleb NN. ''The Black Swan.'' New York, New York: Random House; 2007.
*West B, Griffin L. ''Biodynamics: Why the Wirewalker Doesn't Fall.'' Hoboken, New Jersey: John Wiley & Sons, Inc., 2004.
[[Category:Management systems]]
[[Category:Human resource management]]
[[Category:Health]]
[[Category:Organization]]
[[Category:Workforce]]
[[Category:Modeling]]
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